A Network Module for the Perseus Software for Computational Proteomics Facilitates Proteome Interaction Graph Analysis

Proteomics
data analysis strongly benefits from not studying single
proteins in isolation but taking their multivariate interdependence
into account. We introduce PerseusNet, the new Perseus network module
for the biological analysis of proteomics data. Proteomics is commonly
used to generate networks, e.g., with affinity purification experiments,
but networks are also used to explore proteomics data. PerseusNet
supports the biomedical researcher for both modes of data analysis
with a multitude of activities. For affinity purification, a volcano-plot-based
statistical analysis method for network generation is featured which
is scalable to large numbers of baits. For posttranslational modifications
of proteins, such as phosphorylation, a collection of dedicated network
analysis tools helps in elucidating cellular signaling events. Co-expression
network analysis of proteomics data adopts established tools from
transcriptome co-expression analysis. PerseusNet is extensible through
a plugin architecture in a multi-lingual way, integrating analyses
in C#, Python, and R, and is freely available at http://www.perseus-framework.org.